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Statistics and Probability with Applications for Engineers and Scientists, 2nd Edition





Statistics and Probability with Applications for Engineers and Scientists, 2nd Edition

Bhisham C. Gupta, Irwin Guttman, Kalanka Jayalath

ISBN: 978-1-119-51663-7 January 2020 992 Pages



Introduces basic concepts in probability and statistics to data science students, as well as engineers and scientists

Aimed at undergraduate/graduate-level engineering and natural science students, this timely, fully updated edition of a popular book on statistics and probability shows how real-world problems can be solved using statistical concepts. It removes Excel exhibits and replaces them with R software throughout, and updates both MINITAB and JMP software instructions and content. A new chapter discussing data mining—including big data, classification, machine learning, and visualization—is featured. Another new chapter covers cluster analysis methodologies in hierarchical, nonhierarchical, and model based clustering. The book also offers a chapter on Response Surfaces that previously appeared on the book’s companion website.

Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP, Second Edition is broken into two parts. Part I covers topics such as: describing data graphically and numerically, elements of probability, discrete and continuous random variables and their probability distributions, distribution functions of random variables, sampling distributions, estimation of population parameters and hypothesis testing. Part II covers: elements of reliability theory, data mining, cluster analysis, analysis of categorical data, , nonparametric tests, simple and multiple linear regression analysis, analysis of variance, factorial designs, response surfaces, and statistical quality control (SQC) including phase I and phase II control charts. The appendices contain statistical tables and charts and answers to selected problems.  

  • Features two new chapters—one on Data Mining and another on Cluster Analysis
  • Now contains R exhibits including code, graphical display, and some results
  • MINITAB and JMP have been updated to their latest versions
  • Emphasizes the p-value approach and includes related practical interpretations
  • Offers a more applied statistical focus, and features modified examples to better exhibit statistical concepts
  • Supplemented with an Instructor's-only solutions manual on a book’s companion website 

Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP is an excellent text for graduate level data science students, and engineers and scientists. It is also an ideal introduction to applied statistics and probability for undergraduate students in engineering and the natural sciences. 

Preface xxi

1 Introduction 1

Part I

2 Describing Data Graphically and Numerically 11

3 Elements of Probability 103

4 Discrete Random variables and Some Important Discrete Probability Distributions 139

5 Continuous Random Variables and Some Important Continuous Probability Distributions 181

6 Distribution of Functions of Random Variables 255

7 Sampling Distributions 285

8 Estimation of Population Parameters 327

9 Hypothesis Testing 399

Part II

10 Elements of Reliability Theory 505

11 On Data Mining 541

12 Cluster Analysis 587

13 Analysis of Categorical Data 633

14 Nonparametric Tests 667

15 Simple Linear Regression Analysis 699

16 Multiple Linear Regression Analysis 777

17 Analysis of Variance 849

18 The 2k Factorial Designs 941

19 Response Surfaces 993

20 Statistical Quality Control—Phase I Control Charts 1057

21 Statistical Quality Control—Phase II Control Charts 1059